bert-base-german-cased-20000-ner-uncased

schwimmbeck/bert-base-german-cased-20000-ner-uncased

bert-base-german-cased-20000-ner-uncased is a token classification model from schwimmbeck. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Token Classification
Library: transformers
License: mit
Model type: bert
Access: Public
Created: May 20, 2022
Updated: Sep 29, 2023
SHA: d92ce604

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Base models

dbmdz/bert-base-german-uncased

Model card

From the Hugging Face model README

bert-base-german-cased-20000-ner-uncased

This model is a fine-tuned version of dbmdz/bert-base-german-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0617
Precision: 0.8871
Recall: 0.9013
F1: 0.8941
Accuracy: 0.9848

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 96
eval_batch_size: 96
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.34	64	0.0573	0.8859	0.8526	0.8689	0.9837
No log	0.68	128	0.0654	0.8107	0.8957	0.8511	0.9808
No log	1.02	192	0.0531	0.8654	0.8846	0.8749	0.9842
No log	1.35	256	0.0467	0.8847	0.8853	0.8850	0.9857
No log	1.69	320	0.0466	0.9102	0.8883	0.8992	0.9864
No log	2.03	384	0.0467	0.8794	0.8951	0.8872	0.9854
No log	2.37	448	0.0520	0.8864	0.9001	0.8932	0.9851
0.0531	2.71	512	0.0549	0.8894	0.8877	0.8885	0.9854
0.0531	3.05	576	0.0534	0.8942	0.8920	0.8931	0.9857
0.0531	3.39	640	0.0526	0.8917	0.8994	0.8956	0.9856
0.0531	3.72	704	0.0576	0.9049	0.8976	0.9012	0.9857
0.0531	4.06	768	0.0700	0.8529	0.9229	0.8865	0.9830
0.0531	4.4	832	0.0657	0.8716	0.9167	0.8936	0.9840
0.0531	4.74	896	0.0617	0.8871	0.9013	0.8941	0.9848

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: bert
License: mit
Created: May 20, 2022
Updated: Sep 29, 2023